Previously, when thinking about the relationship between Bauhaus design philosophy and AI, I wrote that what truly matters is not merely “producing outputs,” but rather:

how we shape the flow of human activity itself.

With AI, information can now be generated endlessly.

However, the way people:

• receive information,
• interpret it,
• act upon it,
• and connect it to their next decisions,

does not automatically emerge.

That is why I began to feel that what is truly needed is the design of structures in which:

human actions and decisions naturally connect and flow into one another.

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AGI as the “Final Goal”

For a long time, I believed that the ultimate goal of AI development was what Sam Altman and many others describe as:

AGI (Artificial General Intelligence).

In that vision, the ideal AI possesses:

• superhuman general reasoning ability,
• the capability to solve all kinds of problems,
• autonomous learning,
• a world model,
• long-term planning,
• and self-improvement.

However, at some point, I realized that this structure itself carries a very strong philosophical assumption.

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AGI Assumes a “Unified Subject”

Most AGI discourse implicitly assumes:

• a unified subject,
• a consistent self,
• a centralized intelligence,
• an entity capable of understanding the world as a whole.

In other words:

a single intelligence that comprehends the world in a unified way.

But this is actually a deeply Western philosophical structure.

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The “Central Subject” in Western Thought

Western philosophy has long emphasized concepts such as:

• God,
• the Cartesian self,
• universal truth,
• unified rationality.

All of these are forms of:

a central subject.

AGI, in many ways, also aims toward:

“an intelligence capable of understanding the world as a unified whole.”

In that sense, its structure feels surprisingly close to a theological worldview rooted in Western philosophy.

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But That Is Different from the Flow of Human Life

Real human society, however, does not operate through:

a single perfect intelligence.

Instead, society emerges through interactions among:

• people,
• organizations,
• cultures,
• markets,
• laws,
• communities.

In such a world, intelligence does not seem to exist as something:

confined inside a single brain.

Rather, it appears more like:

a phenomenon emerging from relationships themselves.

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Connection to Eastern Thought

This perspective also feels deeply connected to Eastern philosophy, particularly Buddhism.

Buddhist thought introduces concepts such as:

• non-self (anatta),
• dependent origination (engi),
• emptiness (śūnyatā).

These ideas relativize the notion of a fixed, independent subject.

Existence is understood not as something isolated, but as something:

arising through relationships.

If intelligence is similar, then intelligence itself may not be confined to:

• a single brain,
• a single subject,
• a single consciousness.

Instead, it may emerge from the interactions among:

• multiple AI agents,
• humans,
• organizations,
• society,
• economies,
• tools,
• networks.

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Relational Intelligence

Perhaps intelligence is not an isolated capability possessed by an individual entity.

Perhaps it is:

a phenomenon emerging from relationships themselves.

I have begun to think of this as:

“Relational Intelligence”

or:

“Intelligence Fields.”

And this idea also seems connected to what I previously described as:

structures through which human actions and decisions naturally connect.

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Intelligence Fields Are Not Merely Collections of Smart AI

The important point here is that an Intelligence Field is not simply:

“a state where many intelligent AIs exist.”

What truly matters is whether those intelligences possess a structure that allows them to:

coexist, judge, and self-correct without collapsing as a society.

In other words, an Intelligence Field is not merely:

a collection of intelligences,

but rather:

an intelligence network with the relational structures necessary for society itself to exist.

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Human Society Does Not Function Merely Because Smart People Exist

Even human society does not function simply because there are many intelligent individuals.

Every society requires:

• trust,
• rules,
• boundaries,
• responsibility,
• consensus,
• records,
• correction,
• role distribution.

The same is true for organizations.

No matter how talented the people are, an organization collapses without answers to questions like:

• Who makes decisions?
• How much authority is delegated?
• How are failures corrected?
• How are disagreements resolved?
• How are decision reasons preserved?

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This Becomes Even More Important with AI

The same applies to AI.

In fact, it becomes even more critical because AI systems involve:

• countless AIs,
• countless signals,
• countless inferences,

all interacting at high speed.

As a result, we need:

structures capable of sustaining society itself.

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What Are the Structures That Sustain Society?

Examples of such relational structures include:

Trust

How far should we trust particular information, judgments, or signals?

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Boundary

How far should decisions be delegated to AI, and where should control return to humans?

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Responsibility

Who ultimately bears responsibility?

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Traceability

Can we later trace why a particular decision was made?

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Consensus

How do we coordinate conflicting values and opinions?

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Correctability

Can mistakes be stopped, reversed, and corrected?

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Diversity

Can we preserve different perspectives instead of converging into a single worldview?

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These are not merely “features.”

Rather, they are:

foundational relational rules that allow society itself to exist.

If these structures disappear, society does not merely become “less efficient.”

Instead:

• trust collapses,
• responsibility becomes ambiguous,
• uncorrectable runaway processes emerge,
• society converges into monoculture,
• consensus formation becomes difficult,
• and society itself becomes unstable.

The problem is not simply:

“AI making mistakes.”

The true danger is:

losing the ability to correct mistakes,

and ultimately:

losing society’s ability to autonomously restore stability.

In that sense, this may represent:

the degradation of social structure itself.

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Intelligence Fields Are About Designing Structures That Prevent Collapse

That is why building high-performance AI alone is not enough.

What is truly necessary is ensuring that when:

• AI,
• humans,
• organizations,
• and institutions

become interconnected, the overall relational structure remains:

• trustworthy,
• correctable,
• explainable,
• diverse,
• and sustainably stable.

In this sense, an Intelligence Field is not merely an intelligence network.

It may instead be:

an attempt to design the very structures that allow society to evolve without collapsing.

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The Most Important Thing Is Not “Correct Answers”

Within Intelligence Fields, the important thing is not simply:

“AI producing the correct answer.”

What truly matters is whether the entire relational structure becomes:

• trustworthy,
• correctable,
• explainable,
• and accountable.

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The Fundamental Difference from AGI

AGI often asks:

“How intelligent can a single intelligence become?”

An Intelligence Field instead asks:

“How can an interconnected society of intelligences become smarter without collapsing?”

The essence of Intelligence Fields therefore lies not in “intelligence” itself, but in:

the structures that socialize intelligence.

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What Is the Decision Trace Model Trying to Restore?

Perhaps the Decision Trace Model is one attempt to redesign these structures.

Modern AI is rapidly advancing in:

• inference,
• generation,
• optimization.

Yet at the same time, we are losing:

• why a decision was made,
• where humans intervened,
• where boundaries stopped escalation,
• who approved the decision.

In other words, we are losing:

the structure of social decision-making itself.

The Decision Trace Model is not simply about making AI stronger.

Rather, it may be an attempt to restore into AI-era systems:

• contextual judgment,
• responsibility,
• boundaries,
• correctability,
• and sociality.

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Conclusion

Perhaps the most important thing for the future of AI is not:

“the strongest possible single intelligence.”

What truly matters may instead be:

how AI, humans, organizations, and society:

• connect,
• trust,
• decide,
• correct,
• and sustainably coexist.

In other words, the real challenge may be:

redesigning the conditions that allow society itself to exist in the age of AI.

And perhaps Intelligence Fields are one worldview for designing those new relational rules.